Meeting Abstract
Understanding evolution, in part, requires understanding how variation will change the functional performance of biological structures. Variation provides the raw material on which natural selection acts to shape these structures, but the performance consequences of variation are difficult to predict in complex, non-linear functional systems. Computational models have long been used to better understand the biomechanics of biological structures, but their usefulness has been historically limited in informing studies of evolution. This work strives to integrate the detailed, computational models with studies of evolution and morphological diversity through unique quantitative analysis tools. We apply uncertainty quantification to simple computational models of three functional systems involving fluid-structure interactions: odor-capture by crustacean antennules, blood-pumping by the tubular hearts of tunicates, and gliding performance in birds. We use generalized polynomial chaos expansions in conjunction with Sobol indices to assess and describe the role of variation in the performance of each system across a wide morphological and kinematic space. From these techniques, we infer the strength of physical constraints on the evolution of biological structures in each system.
